We model data collections where the members of the collection are comparable to each other via some similarity measure. The central idea is to define a card abstraction for each member of the collection. Each card contains condensed information describing the main characteristics of a particular collection member. The card collection can be interactively explored, by via window panning, zooming, and mouse hovering, dragging and clicking. The system also offers a card trading mechanism where users can virtually buy or sell collection cards. Cards have a value that is dynamically computed as a function of several parameters that include their popularity, demand, and level of similarity to other cards in the collection.

We have tested our current implementation with several data bases including the DIMACS REU projects since 1996, the 2014 Soccer World Cup, and the Carnegie Mellon NEEL Learning system.

This is Joint work with J. Abello. The REU portion is joint work with the REU students M. Sumida, A. Arredondo, Jose Ramirez, and Ram Hari Dahal.